Showing 1–10 of 10 results for author: Kasera, S K

Two Measure is Two Know: Calibration-free Full Duplex Monitoring for Software Radio Platforms

Authors: Jie Wang, Jonathan Gornet, Alex Orange, Leigh Stoller, Gary Wong, Jacobus Van Der Merwe, Sneha Kumar Kasera, Neal Patwari

Abstract: Future virtualized radio access network (vRAN) infrastructure providers (and today's experimental wireless testbed providers) may be simultaneously uncertain what signals are being transmitted by their base stations and legally responsible for their violations. These providers must monitor the spectrum of transmissions and external signals without access to the radio itself. In this paper, we prop… ▽ More Future virtualized radio access network (vRAN) infrastructure providers (and today's experimental wireless testbed providers) may be simultaneously uncertain what signals are being transmitted by their base stations and legally responsible for their violations. These providers must monitor the spectrum of transmissions and external signals without access to the radio itself. In this paper, we propose FDMonitor, a full-duplex monitoring system attached between a transmitter and its antenna to achieve this goal. Measuring the signal at this point on the RF path is necessary but insufficient since the antenna is a bidirectional device. FDMonitor thus uses a bidirectional coupler, a two-channel receiver, and a new source separation algorithm to simultaneously estimate the transmitted signal and the signal incident on the antenna. Rather than requiring an offline calibration, we also adaptively estimate the linear model for the system on the fly. FDMonitor has been running on a real-world open wireless testbed, monitoring 19 SDR platforms controlled (with bare metal access) by outside experimenters over a seven month period, sending alerts whenever a violation is observed. Our experimental results show that FDMonitor accurately separates signals across a range of signal parameters. Over more than 7 months of observation, it achieves a positive predictive value of 97%, with a total of 20 false alerts. △ Less

Submitted 15 December, 2022; originally announced December 2022.

Hiding Signal Strength Interference from Outside Adversaries

Authors: Mingxuan Han, Jeff M. Phillips, Sneha Kumar Kasera

Abstract: The presence of people can be detected by passively observing the signal strength of Wifi and related forms of communication. This paper tackles the question of how and when can this be prevented by adjustments to the transmitted signal strength, and other similar measures. The main contribution of this paper is a formal framework to analyze this problem, and the identification of several scenario… ▽ More The presence of people can be detected by passively observing the signal strength of Wifi and related forms of communication. This paper tackles the question of how and when can this be prevented by adjustments to the transmitted signal strength, and other similar measures. The main contribution of this paper is a formal framework to analyze this problem, and the identification of several scenarios and corresponding protocols which can prevent or limit the inference from passive signal strength snooping. △ Less

Submitted 20 December, 2021; originally announced December 2021.

Comments: 6 pages, 2 figures

A Q-Learning-based Approach for Distributed Beam Scheduling in mmWave Networks

Authors: Xiang Zhang, Shamik Sarkar, Arupjyoti Bhuyan, Sneha Kumar Kasera, Mingyue Ji

Abstract: We consider the problem of distributed downlink beam scheduling and power allocation for millimeter-Wave (mmWave) cellular networks where multiple base stations (BSs) belonging to different service operators share the same unlicensed spectrum with no central coordination or cooperation among them. Our goal is to design efficient distributed beam scheduling and power allocation algorithms such that… ▽ More We consider the problem of distributed downlink beam scheduling and power allocation for millimeter-Wave (mmWave) cellular networks where multiple base stations (BSs) belonging to different service operators share the same unlicensed spectrum with no central coordination or cooperation among them. Our goal is to design efficient distributed beam scheduling and power allocation algorithms such that the network-level payoff, defined as the weighted sum of the total throughput and a power penalization term, can be maximized. To this end, we propose a distributed scheduling approach to power allocation and adaptation for efficient interference management over the shared spectrum by modeling each BS as an independent Q-learning agent. As a baseline, we compare the proposed approach to the state-of-the-art non-cooperative game-based approach which was previously developed for the same problem. We conduct extensive experiments under various scenarios to verify the effect of multiple factors on the performance of both approaches. Experiment results show that the proposed approach adapts well to different interference situations by learning from experience and can achieve higher payoff than the game-based approach. The proposed approach can also be integrated into our previously developed Lyapunov stochastic optimization framework for the purpose of network utility maximization with optimality guarantee. As a result, the weights in the payoff function can be automatically and optimally determined by the virtual queue values from the sub-problems derived from the Lyapunov optimization framework. △ Less

Submitted 16 October, 2021; originally announced October 2021.

Comments: 10 pages

Uncoordinated Spectrum Sharing in Millimeter Wave Networks Using Carrier Sensing

Authors: Shamik Sarkar, Xiang Zhang, Arupjyoti Bhuyan, Mingyue Ji, Sneha Kumar Kasera

Abstract: We propose using Carrier Sensing (CS) for distributed interference management in millimeter-wave (mmWave) cellular networks where spectrum is shared by multiple operators that do not coordinate among themselves. In addition, even the base station sites can be shared by the operators. We describe important challenges in using traditional CS in this setting and propose enhanced CS protocols to addre… ▽ More We propose using Carrier Sensing (CS) for distributed interference management in millimeter-wave (mmWave) cellular networks where spectrum is shared by multiple operators that do not coordinate among themselves. In addition, even the base station sites can be shared by the operators. We describe important challenges in using traditional CS in this setting and propose enhanced CS protocols to address these challenges. Using stochastic geometry, we develop a general framework for downlink coverage probability analysis of our shared mmWave network in the presence of CS and derive the downlink coverage probability expressions for several CS protocols. To the best of our knowledge, our work is the first to investigate and analyze (using stochastic geometry) CS for mmWave networks with spectrum and BS sites shared among non-coordinating operators. We evaluate the downlink coverage probability of our shared mmWave network using simulations as well as numerical examples based on our analysis. Our evaluations show that our proposed enhancements lead to an improvement in downlink coverage probability, compared to the downlink coverage probability with no CS, for higher values of signal-to-interference and noise ratio (SINR). Interestingly, our evaluations also reveal that for lower values of SINR, not using any CS is the best strategy in terms of the downlink coverage probability. △ Less

Submitted 24 February, 2021; originally announced February 2021.

A Non-cooperative Game-based Distributed Beam Scheduling Framework for 5G Millimeter-Wave Cellular Networks

Authors: Xiang Zhang, Shamik Sarkar, Arupjyoti Bhuyan, Sneha Kumar Kasera, Mingyue Ji

Abstract: This paper studies the problem of distributed beam scheduling for 5G millimeter-Wave (mm-Wave) cellular networks where base stations (BSs) belonging to different operators share the same spectrum without centralized coordination among them. Our goal is to design efficient distributed scheduling algorithms to maximize the network utility, which is a function of the achieved throughput by the user e… ▽ More This paper studies the problem of distributed beam scheduling for 5G millimeter-Wave (mm-Wave) cellular networks where base stations (BSs) belonging to different operators share the same spectrum without centralized coordination among them. Our goal is to design efficient distributed scheduling algorithms to maximize the network utility, which is a function of the achieved throughput by the user equipment (UEs), subject to the average and instantaneous power consumption constraints of the BSs. We propose a Media Access Control (MAC) and a power allocation/adaptation mechanism utilizing the Lyapunov stochastic optimization framework and non-cooperative games. In particular, we first decompose the original utility maximization problem into two sub-optimization problems for each time frame, which are a convex optimization problem and a non-convex optimization problem, respectively. By formulating the distributed scheduling problem as a non-cooperative game where each BS is a player attempting to optimize its own utility, we provide a distributed solution to the non-convex sub-optimization problem via finding the Nash Equilibrium (NE) of the game whose weights are determined optimally by the Lyapunov optimization framework. Finally, we conduct simulation under various network settings to show the effectiveness of the proposed game-based beam scheduling algorithm in comparison to that of several reference schemes. △ Less

Submitted 22 July, 2021; v1 submitted 21 December, 2020; originally announced December 2020.

Comments: 40 pages, 9 figures

Quantifying Interference-Assisted Signal Strength Surveillance of Sound Vibrations

Authors: Alemayehu Solomon Abrar, Neal Patwari, Sneha Kumar Kasera

Abstract: A malicious attacker could, by taking control of internet-of-things devices, use them to capture received signal strength (RSS) measurements and perform surveillance on a person's vital signs, activities, and sound in their environment. This article considers an attacker who looks for subtle changes in the RSS in order to eavesdrop sound vibrations. The challenge to the adversary is that sound vib… ▽ More A malicious attacker could, by taking control of internet-of-things devices, use them to capture received signal strength (RSS) measurements and perform surveillance on a person's vital signs, activities, and sound in their environment. This article considers an attacker who looks for subtle changes in the RSS in order to eavesdrop sound vibrations. The challenge to the adversary is that sound vibrations cause very low amplitude changes in RSS, and RSS is typically quantized with a significantly larger step size. This article contributes a lower bound on an attacker's monitoring performance as a function of the RSS step size and sampling frequency so that a designer can understand their relationship. Our bound considers the little-known and counter-intuitive fact that an adversary can improve their sinusoidal parameter estimates by making some devices transmit to add interference power into the RSS measurements. We demonstrate this capability experimentally. As we show, for typical transceivers, the RSS surveillance attacker can monitor sound vibrations with remarkable accuracy. New mitigation strategies will be required to prevent RSS surveillance attacks. △ Less

Submitted 21 February, 2020; originally announced February 2020.

Comments: arXiv admin note: substantial text overlap with arXiv:1905.03939

Quantifying an Interference-Assisted Signal Strength Breathing Surveillance Attack

Authors: Alemayehu Solomon Abrar, Neal Patwari, Aniqua Baset, Sneha Kumar Kasera

Abstract: A malicious attacker could, by taking control of internet-of-things devices, use them to capture received signal strength (RSS) measurements and perform surveillance on a person's vital signs, activities, audio in their environment, and other RF sensing capabilities. This paper considers an attacker who looks for periodic changes in the RSS in order to surveil a person's breathing rate. The challe… ▽ More A malicious attacker could, by taking control of internet-of-things devices, use them to capture received signal strength (RSS) measurements and perform surveillance on a person's vital signs, activities, audio in their environment, and other RF sensing capabilities. This paper considers an attacker who looks for periodic changes in the RSS in order to surveil a person's breathing rate. The challenge to the attacker is that a person's breathing causes a low amplitude change in RSS, and RSS is typically quantized with a significantly larger step size. This paper contributes a lower bound on an attacker's breathing monitoring performance as a function of the RSS step size and sampling frequency so that a designer can understand their relationship. Our bound considers the little-known and counter-intuitive fact that an adversary can improve their sinusoidal parameter estimates by making some devices transmit to add interference power into the RSS measurements. We demonstrate this capability experimentally. As we show, for typical transceivers, the RSS surveillance attack can monitor RSS with remarkable accuracy. New mitigation strategies will be required to prevent RSS surveillance attacks. △ Less

Submitted 10 May, 2019; originally announced May 2019.

Profitable Task Allocation in Mobile Cloud Computing

Authors: Mojgan Khaledi, Mehrdad khaledi, Sneha Kumar Kasera

Abstract: We propose a game theoretic framework for task allocation in mobile cloud computing that corresponds to offloading of compute tasks to a group of nearby mobile devices. Specifically, in our framework, a distributor node holds a multidimensional auction for allocating the tasks of a job among nearby mobile nodes based on their computational capabilities and also the cost of computation at these nod… ▽ More We propose a game theoretic framework for task allocation in mobile cloud computing that corresponds to offloading of compute tasks to a group of nearby mobile devices. Specifically, in our framework, a distributor node holds a multidimensional auction for allocating the tasks of a job among nearby mobile nodes based on their computational capabilities and also the cost of computation at these nodes, with the goal of reducing the overall job completion time. Our proposed auction also has the desired incentive compatibility property that ensures that mobile devices truthfully reveal their capabilities and costs and that those devices benefit from the task allocation. To deal with node mobility, we perform multiple auctions over adaptive time intervals. We develop a heuristic approach to dynamically find the best time intervals between auctions to minimize unnecessary auctions and the accompanying overheads. We evaluate our framework and methods using both real world and synthetic mobility traces. Our evaluation results show that our game theoretic framework improves the job completion time by a factor of 2-5 in comparison to the time taken for executing the job locally, while minimizing the number of auctions and the accompanying overheads. Our approach is also profitable for the nearby nodes that execute the distributor's tasks with these nodes receiving a compensation higher than their actual costs. △ Less

Submitted 30 August, 2016; originally announced August 2016.

Monitoring Breathing via Signal Strength in Wireless Networks

Authors: Neal Patwari, Joey Wilson, Sai Ananthanarayanan P. R., Sneha K. Kasera, Dwayne Westenskow

Abstract: This paper shows experimentally that standard wireless networks which measure received signal strength (RSS) can be used to reliably detect human breathing and estimate the breathing rate, an application we call "BreathTaking". We show that although an individual link cannot reliably detect breathing, the collective spectral content of a network of devices reliably indicates the presence and rate… ▽ More This paper shows experimentally that standard wireless networks which measure received signal strength (RSS) can be used to reliably detect human breathing and estimate the breathing rate, an application we call "BreathTaking". We show that although an individual link cannot reliably detect breathing, the collective spectral content of a network of devices reliably indicates the presence and rate of breathing. We present a maximum likelihood estimator (MLE) of breathing rate, amplitude, and phase, which uses the RSS data from many links simultaneously. We show experimental results which demonstrate that reliable detection and frequency estimation is possible with 30 seconds of data, within 0.3 breaths per minute (bpm) RMS error. Use of directional antennas is shown to improve robustness to motion near the network. △ Less

Submitted 18 September, 2011; originally announced September 2011.

Channel Sounding for the Masses: Low Complexity GNU 802.11b Channel Impulse Response Estimation

Authors: Mohammad H. Firooz, Dustin Maas, Junxing Zhang, Neal Patwari, Sneha K. Kasera

Abstract: New techniques in cross-layer wireless networks are building demand for ubiquitous channel sounding, that is, the capability to measure channel impulse response (CIR) with any standard wireless network and node. Towards that goal, we present a software-defined IEEE 802.11b receiver and CIR estimation system with little additional computational complexity compared to 802.11b reception alone. The sy… ▽ More New techniques in cross-layer wireless networks are building demand for ubiquitous channel sounding, that is, the capability to measure channel impulse response (CIR) with any standard wireless network and node. Towards that goal, we present a software-defined IEEE 802.11b receiver and CIR estimation system with little additional computational complexity compared to 802.11b reception alone. The system implementation, using the universal software radio peripheral (USRP) and GNU Radio, is described and compared to previous work. By overcoming computational limitations and performing direct-sequence spread-spectrum (DS-SS) matched filtering on the USRP, we enable high-quality yet inexpensive CIR estimation. We validate the channel sounder and present a drive test campaign which measures hundreds of channels between WiFi access points and an in-vehicle receiver in urban and suburban areas. △ Less

Submitted 20 July, 2010; originally announced July 2010.